Umfang:
1 Online-Ressource (circa 42 Seiten)
,
Illustrationen
ISBN:
9781484310908
Serie:
IMF staff discussion note SDN/17, 06 (September 2017)
Inhalt:
Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe Hammer, Cornelia Big Data: Potential, Challenges and Statistical Implications Washington, D.C. : International Monetary Fund, 2017 ISBN 9781484310908
Sprache:
Englisch
Schlagwort(e):
Graue Literatur
DOI:
10.5089/9781484310908.006
URL:
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